Predicting the Solubility of Inorganic Ion Pairs in Water

Rahman, Tasnim; Petrus, Enric; Segado, Mireia; Martin, Nicolas P.; Palys, Lauren N.; Rambaran, Mark A.; Ohlin, C. Andre; Bo, Carles; Nyman, May

doi:10.1002/anie.202117839

Title: Predicting the Solubility of Inorganic Ion Pairs in Water

Journal Article · 10 February 2022 · Angewandte Chemie (International Edition)

DOI: https://doi.org/10.1002/anie.202117839 · OSTI ID:1976280

Rahman, Tasnim ^[1]; Petrus, Enric ^[2]; Segado, Mireia ^[2]; Martin, Nicolas P. ^[3]; Palys, Lauren N. ^[3]; Rambaran, Mark A. ^[4]; Ohlin, C. Andre ^[4]; Bo, Carles ^[5];

^[3]

Oregon State University, Corvallis, OR (United States); OSTI
Barcelona Institute of Science & Technology (BIST), Tarragona (Spain)
Oregon State University, Corvallis, OR (United States)
Umea University (Sweden)
Barcelona Institute of Science & Technology (BIST), Tarragona (Spain); Universitat Rovira i Virgili (URV), Tarragona (Spain)

Polyoxometalates (POMs), ranging in size from 1 to 10’s of nanometers, resemble building blocks of inorganic materials. Elucidating their complex solubility behavior with alkali-counterions can inform natural and synthetic aqueous processes. Here in the study of POMs ([Nb₂₄O₇₂H₉]^15-, Nb₂₄) we discovered an unusual solubility trend (termed anomalous solubility) of alkali-POMs, in which Nb₂₄ is most soluble with the smallest (Li⁺) and largest (Rb/Cs⁺) alkalis, and least soluble with Na/K⁺. Via computation, we define a descriptor (σ-profile) and use an artificial neural network (ANN) to predict all three described alkali-anion solubility trends: amphoteric, normal (Li⁺>Na⁺>K⁺>Rb⁺>Cs⁺), and anomalous (Cs⁺>Rb⁺>K⁺>Na⁺>Li⁺). Testing predicted amphoteric solubility affirmed the accuracy of the descriptor, provided solution-phase snapshots of alkali–POM interactions, yielded a new POM formulated [Ti₆Nb₁₄O₅₄]^14-, and provides guidelines to exploit alkali–POM interactions for new POMs discovery.

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Research Organization:: Oregon State University, Corvallis, OR (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division (MSE); Spanish Ministry of Science and Innovation; Severo Ochoa Excellence Accreditation; Catalan Institute of Chemical Research (ICIQ); Murdock Charitable Trust; Swedish Research Council; Kempe Foundation

Grant/Contract Number:: SC0010802

OSTI ID:: 1976280

Alternate ID(s):: OSTI ID: 1846505

Journal Information:: Angewandte Chemie (International Edition), Journal Name: Angewandte Chemie (International Edition) Journal Issue: 19 Vol. 61; ISSN 1433-7851

Publisher:: WileyCopyright Statement

Country of Publication:: United States

Language:: English

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Related Subjects

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
polyoxometalate
polyoxoniobate
ion-pairing
SAXS
solubility
machine learning

CSD 2118401: Experimental Crystal Structure Determination Tasnim, Rahman,; Enric, Petrus,; Mireia, Segado, https://doi.org/10.25505/fiz.icsd.cc293cjb The current record is supplemented by this dataset	dataset	January 2022
CSD 2118399: Experimental Crystal Structure Determination Tasnim, Rahman,; Enric, Petrus,; Mireia, Segado, https://doi.org/10.25505/fiz.icsd.cc293cg8 The current record is supplemented by this dataset	dataset	January 2022
CCDC 2118398: Experimental Crystal Structure Determination Tasnim, Rahman,; Enric, Petrus,; Mireia, Segado, https://doi.org/10.5517/ccdc.csd.cc293cf7 The current record is supplemented by this dataset	dataset	January 2022
CSD 2118403: Experimental Crystal Structure Determination Tasnim, Rahman,; Enric, Petrus,; Mireia, Segado, https://doi.org/10.25505/fiz.icsd.cc293cld The current record is supplemented by this dataset	dataset	January 2022
CSD 2118402: Experimental Crystal Structure Determination Tasnim, Rahman,; Enric, Petrus,; Mireia, Segado, https://doi.org/10.25505/fiz.icsd.cc293ckc The current record is supplemented by this dataset	dataset	January 2022
CSD 2118400: Experimental Crystal Structure Determination Tasnim, Rahman,; Enric, Petrus,; Mireia, Segado, https://doi.org/10.25505/fiz.icsd.cc293ch9 The current record is supplemented by this dataset	dataset	January 2022

Title: Predicting the Solubility of Inorganic Ion Pairs in Water

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